Is Opencv Python Safe?
Opencv Python — Nerq Trust Score 80.8/100 (A- grade). Score based on 2 independent trust signals. Last analyzed: 2026-04-12
Opencv Python is a Python package with a Nerq Trust Score of 80.8/100 (A-), based on 3 independent data dimensions. Last analyzed: 2026-04-12 Security: 90/100. Popularity: 100/100. Data sourced from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-04-12. Machine-readable data (JSON).
Is Opencv Python safe?
Trust Score Breakdown — Opencv Python has a Nerq Trust Score of 80.8/100 (A-). Measured across 2 independent trust signals (as of 2026-04-12).
What is Opencv Python's trust score?
Opencv Python has a Nerq Trust Score of 80.8/100, earning a A- grade. This score is based on 2 independently measured dimensions including security, maintenance, and community adoption.
What are the key security findings for Opencv Python?
Opencv Python's strongest signal is popularity at 100/100. No known vulnerabilities have been detected.
What is Opencv Python and who maintains it?
| Author | OpenCV Team |
| Category | Python Packages |
| Source | N/A |
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Safety Guide: Opencv Python
What is Opencv Python?
Opencv Python is a Python package — Wrapper package for OpenCV python bindings..
How to Verify Safety
Run pip audit or safety check. Review on PyPI for download stats.
You can also check the trust score via API: GET /v1/preflight?target=opencv-python
Key Safety Concerns for Python package
When evaluating any Python package, watch for: dependency vulnerabilities, malicious uploads, maintenance status.
Measured Signals
Opencv Python has a Nerq Trust Score of 81/100 (A-). This score is a composite of automated measurements of security, maintenance, community, and quality signals.
Key Takeaways
- Opencv Python has a Trust Score of 81/100 (A-).
- The score is a measured composite — it is not a suitability judgment. Evaluate the individual signals against your own requirements.
- Query the current measured values via the Nerq API.
Detailed Score Analysis
| Dimension | Score |
|---|---|
| Security | 90/100 |
| Maintenance | 100/100 |
| Popularity | 100/100 |
| Quality | 65/100 |
| Community | 35/100 |
Based on 5 dimensions. Data from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard.
What data does Opencv Python collect?
Opencv Python is a Python package maintained by OpenCV Team. It receives approximately 10,769,842 weekly downloads. Licensed under Apache 2.0.
As a development package, Opencv Python does not directly collect end-user personal data. However, applications built with it may collect data depending on implementation. Privacy score: 80/100.
Review the package's dependencies for potential supply chain risks. Run your package manager's audit command regularly.
Full analysis: Opencv Python Privacy Report · Privacy review
Is Opencv Python secure?
Security score: 90/100. Opencv Python has 0 known vulnerabilities (CVEs) in the National Vulnerability Database. This is a clean record.
Licensed under Apache 2.0, allowing code inspection. Open-source packages allow independent security review of the source code.
Run your package manager's audit command (`npm audit`, `pip audit`, `cargo audit`) to check for known vulnerabilities in your dependency tree.
Full analysis: Opencv Python Security Report
How we calculated this score
Opencv Python's trust score of 80.8/100 (A-) is computed from PyPI registry, GitHub repository, NVD, OSV.dev, and OpenSSF Scorecard. The score reflects 5 independent dimensions: security (90/100), maintenance (100/100), popularity (100/100), quality (65/100), community (35/100). Each dimension is weighted equally to produce the composite trust score.
Nerq analyzes over 7.5 million entities across 26 registries using the same methodology, enabling direct cross-entity comparison. Scores are updated continuously as new data becomes available.
Signals last measured on April 12, 2026. Data version: 1.0.
Full methodology documentation · Machine-readable data (JSON API)
Frequently Asked Questions
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Disclaimer: Nerq trust scores are automated measurements based on publicly available signals. They are not endorsements, verdicts, or guarantees of suitability. Always evaluate the signals against your own requirements.